```                               HYPOTHESIS TESTING

I.  Introduction.
A.  The role of hypothesis testing in the scientific endeavor.
B.  The logic of hypothesis testing.
1.  Begin with a hypothesis based on theory or previous
research.
2.  Collect empirical data to test the hypothesis.
3.  Analyze the data to see if hypothesis is correct.
C.  The relationship between estimation and hypothesis testing.

II.  The steps in hypothesis testing.
1.  A statitistical test must have something to test or
evaluate.  That something is the null hypothesis.
It is typically a simple mathematical or verbal
statement about population parameters such as "the
two variables are independent" or "the two variables
are equal."
2.  The null hypothesis is always stated in the null or
most neutral form.  Typically, this means to state
that two values are equal or that there is no
difference in two values or that there is no
relationship between two variables.
3.  The null may not be what the researcher actually
hypothesizes to be true.  The researcher may actually
hypothesize that there is a difference or that two
values are not equal.  This alternative hypothesis is
called the research hypothesis.
4.  The null is tested because it is easier to evaluate.
5.  If the null is rejected it offers support for the
research hypothesis.
B.  Determine the best statistical test.
1.  Each hypothesis test requires that a test statistic
be calculated.  The test statistic calculated
depends on the type of hypothesis being evaluated.
2.  Underlying each test statistic is sampling
distribution by which the probability of obtaining
certain test statistics can be evaluated.
3.  There are several different sampling distributions.
Thus far we have talked about two:  the z and t
distributions.  Others will be introduced later.
C.  Check the basic assumptions.
1.  Every test statitistic and sampling distribution is
based on certain assumptions.  Some of the most
common assumptions relate to the nature of the
sample (is it a probability sample), the level of
measurement of the variable being analyzed (is it
nominal, ordinal, or interval), and the shape of
the sampling distribution (is it normal).  However,
there are other assumptions as well.
2.  Before performing a statististical test, you must
be certain the assumption on which it is based hold
true.
D.  Select an alpha level (significance level).
1.  Alpha level, sampling error, and probability.
2.  Alpha level as the probability of rejecting a null
hypothesis when it is actually true.
3.  One- and two-tailed tests.
E.  Calculate the test statistic.
F.  Determine the probability associated with the test statistic.
G.  Compare the obtained probability to the alpha level and make a